We know that 70% of our communication is non-verbal, while verbal communication adds another 7%. Yet, interpreting non-verbal communication by humans is a time-consuming and highly subjective process. For this presentation, we show how machine learning is making qualitative concept testing more efficient, more scalable, and more objective. We demonstrate how the latest cloud computing and machine learning technologies of emotion analytics and text mining were applied in the process of qualitative in-depth interviewing. The combination of the two methods help observe nuanced consumer responses that never before were capable of being observed and compared by humans.